Will Larson's Web Page

Current version of my urban decline paper:

Housing and Labor Market Dynamics in Growing Versus Declining Cities

William D. Larson
George Washington University
Monroe Hall #340
2115 G St NW
Washington, DC 20052
Tel: (202) 557-9930
Fax: (202) 994-6147
Email: larsonwd@gmail.com

Abstract:

This paper reconciles a debate on the nature of regional supply responses to demand shocks. Results imply that demand-driven models are appropriate in growing or stable cities, and models with supply constraints are more appropriate in declining cities. Cities are found to exhibit dramatically different housing and labor market dynamics in response to local demand shocks, consistent with the hypothesis that the durable nature of the housing stock acts as a supply constraint in declining cities.  Failure to apply the correct class of models to a particular city will result in biased estimated employment, house price, and wage effects of both market-based demand shocks and demand-side stimulus policies.

JEL Classifications: R23, R31, R58.

Keywords: housing supply, urban decline, export prices, development policies

I thank Anthony Yezer, Fred Joutz, Donald Parsons, and Tara Sinclair for their untiring help and support. I also thank Timothy Bartik, Joshua Gallin, Joe Gyourko, Mike Hollar, Lutz Kilian, Steve Malpezzi,  Raven Saks Molloy, Mike Owyang, and Albert Saiz for their helpful data, programs, conversations, and correspondence. I would also like to thank seminar participants at the George Washington University and the AREUEA session at 2011 ASSA meetings.

Research Update

First, the “Energy Footprint” paper has been accepted by the Journal of Urban Economics. You can find the accepted version here.

Second, Paul Carrillo, Erik de Wit, and I have finished a draft on a paper entitled, “Can Tightness in the Housing Market Help Predict Subsequent Home Price Appreciation? Evidence from the US and the Netherlands.”  A version of this paper was presented at the 2012 AREUEA mid-year meetings. A draft for circulation is forthcoming. Below is the abstract.

The literature has documented and rationalized a positive correlation between volume of sales and appreciation rates in the housing market. Moreover, home appreciation rates have shown to be persistent and predictable over time. In this study, we test the predictive power of variables that measure market tightness on future home prices. A stylized search-and-matching model is used to illustrate that indicators that measure market tightness, such as sale probabilities and seller’s bargaining power, can be associated with future home price appreciation. The empirical analysis uses Multiple Listing Services data from the Netherlands and from Fairfax County, VA, that contain all residential units offered for sale through a real estate broker over a 15 year period. The individual records are used to construct quarterly aggregate measures of housing conditions in about 40 regions in the Netherlands and in 41 zip codes in Fairfax County.  Besides home price indices, the indicators include an index that measures seller’s bargaining power and the (quality adjusted) probability that a home sells in less than 2 weeks. Conventional time-series models are then used to show that observed changes in sale rates and bargaining power can significantly reduce home price appreciation forecast errors.

Latex seminar

This note is an addendum to the seminar on Latex I’m giving at GWU on April 13, 2011.

• Document template (pdf, tex, gif, eps, xls)
• Bibtex template (tex)
• Beamer presentation (pdf, tex, gif, eps)
• Dissertation template (fits with GW formatting guidelines!)
• post-script to pdf
• images to eps
• excel to tables
• Compiler and package manager: Miktex
• Text Editor (with Latex compiler shortcuts): LEd

Vox EU Article

NBER working paper released

http://www.nber.org/papers/w15455

Is Newer Better? Penn World Table Revisions and Their Impact on Growth Estimates

Simon Johnson, William Larson, Chris Papageorgiou, Arvind Subramanian

This paper sheds light on two problems in the Penn World Table (PWT) GDP estimates. First, we show that these estimates vary substantially across different versions of the PWT despite being derived from very similar underlying data and using almost identical methodologies; that this variability is systematic; and that it is intrinsic to the methodology deployed by the PWT to estimate growth rates. Moreover, this variability matters for the cross-country growth literature. While growth studies that use low frequency data remain robust to data revisions, studies that use annual data are less robust. Second, the PWT methodology leads to GDP estimates that are not valued at purchasing power parity (PPP) prices. This is surprising because the raison d’etre of the PWT is to adjust national estimates of GDP by valuing output at common international (purchasing power parity [PPP]) prices so that the resulting PPP-adjusted estimates of GDP are comparable across countries. We propose an approach to address these two problems of variability and valuation.